Journal of Advanced Information Technology and Convergence (한국정보기술학회 영문논문지)

Korean Institute of Information Technology (한국정보기술학회)
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A New Denoising Method for Time-lapse Video using Background Modeling

  • Park, Sanghyun (Dept. Of Multimedia Engineering, Sunchon National University)
  • Received : 2020.12.10
  • Accepted : 2020.12.29
  • Published : 2020.12.31
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Abstract

Due to the development of camera technology, the cost of producing time-lapse video has been reduced, and time-lapse videos are being applied in many fields. Time-lapse video is created using images obtained by shooting for a long time at long intervals. In this paper, we propose a method to improve the quality of time-lapse videos monitoring the changes in plants. Considering the characteristics of time-lapse video, we propose a method of separating the desired and unnecessary objects and removing unnecessary elements. The characteristic of time-lapse videos that we have noticed is that unnecessary elements appear intermittently in the captured images. In the proposed method, noises are removed by applying a codebook background modeling algorithm to use this characteristic. Experimental results show that the proposed method is simple and accurate to find and remove unnecessary elements in time-lapse videos.

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References

  1. S. Kwon, Y. Kim, C. Son, and W. Kim, "The Design of Platform for Ecotourism Information Supply," Journal of the Korea Institute of Electronic Communication Science, Vol. 13, No. 2, pp. 419-426, Apr. 2018. https://doi.org/10.13067/JKIECS.2018.13.2.419
  2. I. Lee, "Visual Effect and Application of Stereoscopic 3D Image Using Timelapse," Korea Science & Art Forum, Vol. 18, pp. 509-518, Dec. 2014. https://doi.org/10.17548/ksaf.2014.12.18.509
  3. Y. Choi and S. Hong, "The Development and Application Effects of Life Cycle of Plants STEAM Program Using Time-Lapse based on Smart Media," Biology Education, Vol. 44, No. 1, pp. 35-48, Jan. 2016. https://doi.org/10.15717/BIOEDU.2016.44.1.35
  4. K. Nakamura, Y. Watanabe, A. Fujiwara, K. Saito, H. Kobayashi, and K. Sezaki, "Plant Phenology Observation by Students Using Time-Lapse Images: Creation of the Environment and Examination of Its Adequacy," Environments, Vol. 5, No. 1, pp. 1-10, Jan. 2018. https://doi.org/10.3390/environments5010001
  5. M. Vollmer and K. Mollmann, "Time-lapse videos for physics education: specific examples," Physics Education, Vol. 53, No. 3, pp. 1-11, May 2018.
  6. O. Kwon, "Image Shaking Stabilization for Time-lapse Video Making Using Vertical Beam Distance," Journal of Knowledge Information Technology and Systems, Vol. 12, No. 1, pp. 23-31, Jan. 2017. https://doi.org/10.34163/jkits.2017.12.1.003
  7. M. Nones, R. Archetti, and M. Guerrero, "Time-Lapse Photography of the Edge-of-Water Line Displacements of a Sandbar as a Proxy of Riverine Morphodynamics," Water, Vol. 10, No. 5, pp. 1-19, May 2018. https://doi.org/10.3390/w10050604
  8. J. Choi, Y. Baek, and J. Choi, "Robust Salient Moving Object Detection with Light-Computational Load," IFAC Proceedings Volumes, Vol. 41, No. 2, pp. 2371-2376, Feb. 2008. https://doi.org/10.3182/20080706-5-KR-1001.00400
  9. J. Park and D. Kang, "Real-time Circumstances Monitoring System using Background Modeling and Modified CAMShift," The Journal of Korean Institute of Information Technology, Vol. 9, No. 3, pp. 207-212, Mar. 2011.
  10. J. Park and D. Kang, "An Approach to the Fast ROI Detection System using Region Descriptor and Background Modeling," Journal of Advanced Information Technology and Convergence, Vol. 1, No. 1, pp. 9-17, Jul. 2011.
  11. K. Kim, T. Chalidabhongse, D. Harwood, L. Davis, "Real-time foreground-background segmentation using codebook model," Real-Time Imaging, Vol. 11, No. 3, pp. 172-185, Mar. 2005. https://doi.org/10.1016/j.rti.2004.12.004
  12. J. Jung, "Codebook-Based Foreground-Background Segmentation with Background Model Updating," Journal of Digital Contents Society, Vol. 17, No. 5, pp. 375-381, May 2016. https://doi.org/10.9728/DCS.2016.17.5.375
  13. C. Chang, T. Chia, and C. Yang, "Modified temporal difference method for change detection," Optical Engineering, Vol. 44, No. 2, pp. 28-31, Feb. 2005.
  14. L. Marti-Lopez, H. Cabrera, R. Martinez-Celorio, and R. Gonzalez-Pena, "Temporal difference method for processing dynamic speckle patterns," Optics Communications, Vol. 283, No. 24, pp. 4972-4977, Dec. 2010. https://doi.org/10.1016/j.optcom.2010.07.073
  15. R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk, "Slic superpixels compared to state-of-the-art superpixel methods," IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 34, No. 11, pp. 2274-2282, Nov. 2012 https://doi.org/10.1109/TPAMI.2012.120
  16. Pexels, http://pexels.com, [accessed: Jul. 01. 2020].